Our ability to measure intrinsic kinetic isotope effects and solve enzymatic transition state (TS) structures provided a major advance in understanding the bond lengths, geometry and electrostatic charges of the TSs of specific enzymes. Electrostatic potential maps of TSs provided blueprints for the design of specific transition state analogues, providing TS analogues for many enzymes with Kd values of fM to pM. TS analysis provides a two-state picture of catalysis, reactants and TSs, as static objects. The application of computational and expenmental protein dynamic measurements to punne nucleoside phosphorylase (PNP) and lactate dehydrogenase (LDH) is revealing a deeper understanding of the fast atomic motions required for chemistry, TS analogue binding, and the slower conformational changes associated with reactant binding, catalytic site reorganization and product release. Heavy enzymes were recently pioneered in this program project and provide a new tool permitting unprecedented insight into dynamic motion both expenmentally and computationally. Replacing natural amino acids in enzymes with those having increased mass (2H, 13C, 15N) changes atomic bond frequencies throughout the protein (heavy enzyme). Heavy enzymes can be probed by computational and experimental approaches to explore how changes in bond vibrational frequency alter catalytic properties. Quantum calculations with human heart LDH predict concerted hydride and proton transfer in the transition state in normal enzyme but sequential transfer in the heavy enzyme. Multiple kinetic isotope effects will resolve these predictions experimentally. Heavy human PNP shows slower on-enzyme chemistry than normal enzyme and computational analysis predicts the loss to be related to coordinated dynamics. With Schwartz, remote mutations will be predicted to correct motions associated with TS formation. Dynamically engineered PNPs will be produced and evaluated. Four loops at the PNP catalytic site contnbute to the active complex and their motions will be individually monitored by specific labels, t-jump (with Callender) and rapid mixing (with Dyer) experiments. Experiments and computation will explore how optimized TS analogues of human PNP conserve protein dynamics while sub-optimal inhibitors freeze certain dynamic conformations. Making loops heavy in PNP will explore local contributions to on-enzyme chemistry. Small, heavy enzymes like dihydrofolate reductase act differently from PNP, suggesting mass effects on loop motion. We will characterize three distinct heavy enzyme dynamic responses by experimental and computational approaches.